目的 分析2013—2024年南京市鼓楼区水痘流行特征及空间分布规律，为优化防控策略及卫生资源配置提供科学依据。方法 收集南京市鼓楼区水痘报告病例数据，采用Joinpoint 5.3.0软件对水痘报告发病率变化趋势进行分析，运用ArcGIS 10.2软件进行全局空间自相关分析并识别热点区域。结果 研究期间累计报告7 649例病例，年均报告发病率为55.99/10万。水痘疫情整体呈上升趋势（AAPC=36.68%，95%CI：27.19%~60.93%）。病例分布有季节性，呈双峰分布，10月至次年1月为主高峰，6月为次高峰，男女性别比1.20∶1，高发人群为学生、幼托儿童和散居儿童，2013—2020年病例中位年龄[8（5，13）岁]低于2021—2024年[15（10，22）岁]（Z=-28.241，P<0.001）。全局空间自相关分析显示，2016—2020年存在显著的空间自相关（P<0.05），呈空间正相关；局部空间自相关分析共探测到17个“高-高”聚集区域，主要集中在主城区人口密度大的街道，与描述性分析中水痘高发区域基本一致。结论 2013—2024年南京市鼓楼区水痘报告发病率总体呈上升趋势，且具有较高的时空聚集性，聚集区域为人口密度大且传播风险高的主城区，水痘高发年龄存在后移趋势，应加强对高峰时段和重点区域的水痘监测，持续开展高危人群水痘疫苗强化接种工作。

Objective To investigate the epidemic characteristics and spatial distribution patterns of varicella in Gulou District of Nanjing from 2013 to 2024, and to provide a scientific basis for optimizing prevention and control strategies and healthcare resource allocation. Methods The data of reported varicella cases in Gulou District of Nanjing were collected. Joinpoint 5.3.0 software was employed to analyze the trend in reported incidence rate of varicella, and ArcGIS 10.2 software was used to perform global spatial autocorrelation analysis and to identify hotspot areas. Results A total of 7 649 varicella cases were reported during the study period, with an average annual reported incidence rate of 55.99/100 000. The varicella outbreak generally showed an upward trend (AAPC=36.68%, 95%CI: 27.19%-60.93%). Case distribution exhibited seasonality, with a bimodal pattern: the primary peak occurred from October to January of the following year, and a secondary peak was observed in June. The male-to-female ratio was 1.20∶1. Crowds classified as students, kindergarten children and scattered children were more likely to suffer from varicella. The median age of patients from 2013 to 2020 [8(5, 13) years] was significantly lower than that from 2021 to 2024 [15(10, 22) years] (Z=-28.241, P<0.001). Global spatial autocorrelation analysis revealed significant spatial autocorrelation from 2016 to 2020 (P<0.05), indicating positive spatial correlation. Local spatial autocorrelation analysis identified a total of 17 “high-high” clustering areas, primarily concentrated in streets with high population density of the main urban area, which was consistent with the high-incidence regions identified by descriptive analysis. Conclusion The reported incidence rate of varicella in Gulou District of Nanjing from 2013 to 2024 shows an overall upward trend and a significant spatial clustering. These clustering areas are predominantly located in the central urban areas characterized by high population density and high transmission risk. The high-risk age for varicella is shifting older. It is recommended to strengthen varicella surveillance during peak periods and in key areas, and to continuously implement varicella vaccination targeting high-risk populations.